Integration of Shale Gas Production Data and Microseismic for Fracture and Reservoir Properties Using Fast Marching Method

2012 ◽  
Author(s):  
Jiang Xie ◽  
Changdong Yang ◽  
Neha Gupta ◽  
Michael J. King ◽  
Akhil Datta-Gupta
Keyword(s):  
Shale Gas ◽  
Gas Production ◽  
Production Data ◽  
Fast Marching Method ◽  
Fast Marching ◽  
Reservoir Properties ◽  
Marching Method

Integration of Shale-Gas-Production Data and Microseismic for Fracture and Reservoir Properties With the Fast Marching Method

SPE Journal ◽  
2014 ◽  
Vol 20 (02) ◽  
pp. 347-359 ◽  
Author(s):  
Jiang Xie ◽  
Changdong Yang ◽  
Neha Gupta ◽  
Michael J. King ◽  
Akhil Datta-Gupta
Keyword(s):  
Shale Gas ◽  
Gas Production ◽  
Production Data ◽  
Hydraulic Fractures ◽  
Fast Marching Method ◽  
Gas Reservoirs ◽  
Fast Marching ◽  
Drainage Volume ◽  
Shale Gas Reservoirs ◽  
Marching Method

Summary We present a novel approach to calculate drainage volume and well performance in shale gas reservoirs by use of the fast marching method (FMM) combined with a geometric pressure approximation. Our approach can fully account for complex fracture-network geometries associated with multistage hydraulic fractures and their impact on the well pressure and rates. The major advantages of our proposed approach are its simplicity, intuitive appeal, and computational efficiency. For example, we can compute and visualize the time evolution of the well-drainage volume for multimillion-cell geologic models in seconds without resorting to reservoir simulation. A geometric approximation of the drainage volume is then used to compute the well rates and the reservoir pressure. The speed and versatility of our proposed approach make it ideally suited for parameter estimation by means of the inverse modeling of shale-gas performance data. We use experimental design to perform the sensitivity analysis to identify the “heavy hitters” and a genetic algorithm (GA) to calibrate the relevant fracture and matrix parameters in shale-gas reservoirs by history matching of production data. In addition to the production data, microseismic information is used to help us constrain the fracture extent and orientation and to estimate the stimulated reservoir volume (SRV). The proposed approach is applied to a fractured shale-gas well. The results clearly show reduced ranges in the estimated fracture parameters and SRV, leading to improved forecasting and reserves estimation.

Probabilistic Estimation of Shale Gas Reserves Implementing Fast Marching Method and Monte Carlo Simulation

2016 ◽  
Author(s):  
Jaejun Kim ◽  
Joe M. Kang ◽  
Yongjun Park ◽  
Seojin Lim ◽  
Changhyup Park ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Shale Gas ◽  
Computing Time ◽  
Gas Production ◽  
Full Scale ◽  
Fast Marching Method ◽  
Fast Marching ◽  
Gas Recovery ◽  
Marching Method

This paper evaluates the estimated ultimate recovery for 10-year operation at a shale gas reservoir, implementing FMM (Fast Marching Method) as a surrogate model of full-scale numerical simulation and Monte Carlo simulation as a tool for accessing the uncertainty of FMM-based proxy parameters. Sensitivity analysis shows the significant properties affecting the gas recovery that are enhanced permeability, matrix permeability, and porosity in sequence. Using the statistical distributions of these parameters, this study determines P10, P50, and P90 of the 10-year cumulative gas production and compares them with the values from full-physics simulations. The computing time based on the proxy model is much smaller than that of the full-scale simulations while the prediction accuracy is acceptable. FMM can forecast the production profiles reliably without time-consuming simulation and the integration of Monte-Carlo simulation is able to evaluate the uncertainty of gas recovery, quantitatively.

Computing Pressure Front Propagation Using the Diffusive-Time-of-Flight in Structured and Unstructured Grid Systems via the Fast-Marching Method

SPE Journal ◽  
2021 ◽  
pp. 1-21
Author(s):  
Hongquan Chen ◽  
Tsubasa Onishi ◽  
Jaeyoung Park ◽  
Akhil Datta-Gupta
Keyword(s):  
Finite Difference ◽  
Analytical Solutions ◽  
Eikonal Equation ◽  
Front Propagation ◽  
Fast Marching Method ◽  
Fast Marching ◽  
Reservoir Properties ◽  
Grid Systems ◽  
Marching Method ◽  
Diffusive Time

Summary Diffusive-time-of-flight (DTOF), representing the travel time of pressure front propagation, has found many applications in unconventional reservoir performance analysis. The computation of DTOF typically involves upwind finite difference of the Eikonal equation and solution using the fast-marching method (FMM). However, the application of the finite difference-based FMM to irregular grid systems remains a challenge. In this paper, we present a novel and robust method for solving the Eikonal equation using finite volume discretization and the FMM. The implementation is first validated with analytical solutions using isotropic and anisotropic models with homogeneous reservoir properties. Consistent DTOF distributions are obtained between the proposed approach and the analytical solutions. Next, the implementation is applied to unconventional reservoirs with hydraulic and natural fractures. Our approach relies on cell volumes and connections (transmissibilities) rather than the grid geometry, and thus can be easily applied to complex grid systems. For illustrative purposes, we present applications of the proposed method to embedded discrete fracture models (EDFMs), dual-porositydual-permeability models (DPDK), and unstructured perpendicular-bisectional (PEBI) grids with heterogeneous reservoir properties. Visualization of the DTOF provides flow diagnostics, such as evolution of the drainage volume of the wells and well interactions. The novelty of the proposed approach is its broad applicability to arbitrary grid systems and ease of implementation in commercial reservoir simulators. This makes the approach well-suited for field applications with complex grid geometry and complex well architecture.

A Generalized Fast Marching Method on Unstructured Triangular Meshes

2013 ◽  
Vol 51 (6) ◽  
pp. 2999-3035 ◽  
Author(s):  
E. Carlini ◽  
M. Falcone ◽  
Ph. Hoch
Keyword(s):  
Fast Marching Method ◽  
Triangular Meshes ◽  
Fast Marching ◽  
Marching Method

scholarly journals Tsunami wave propagation by voronoi diagram

2018 ◽  
Vol 7 (3) ◽  
pp. 1233
Author(s):  
V Yuvaraj ◽  
S Rajasekaran ◽  
D Nagarajan
Keyword(s):  
Wave Propagation ◽  
Voronoi Diagram ◽  
Tsunami Wave ◽  
Fast Marching Method ◽  
Coastal Regions ◽  
Fast Marching ◽  
Tsunami Waves ◽  
The Finite Difference Method ◽  
Run Up ◽  
Marching Method

Cellular automata is the model applied in very complicated situations and complex problems. It involves the Introduction of voronoi diagram in tsunami wave propagation with the help of a fast-marching method to find the spread of the tsunami waves in the coastal regions. In this study we have modelled and predicted the tsunami wave propagation using the finite difference method. This analytical method gives the horizontal and vertical layers of the wave run up and enables the calculation of reaching time.  

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